In a company environment, a large number of systems comprising large amounts of data can be found. Because of the large amount of data, providing information about the knowledge the company has, helps the company to more efficiently use its own knowledge.
The data sources within a company may be, for example, an Enterprise Resource Planning (ERP) database, a Customer Relationship Management (CRM) database, a Manufacturing Execution System (MES) database, some legacy databases, and the filesystem with data files itself, the file system also being denoted as files database, though the file system usually is not a relational database. Many more different databases may be used in a company, based upon its respective specific needs.
The aforementioned databases are usually very specific in nature, because they serve very specific needs of the company. As a result, it is very tedious to get an overview about all data the company has. Methods and processes addressing this problem, in order to provide a base for improving the company's operative or strategic decisions, are summarized under the term of Business Intelligence (BI). Known example results of BI are Online Analytical Processing (OLAP), Data Mining, Data Visualization, or, Reports.
The means for achieving the BI results may be a Corporate Information Factory (CIF), or: a corporate data processing system that comprises a central database that may be termed as Data Warehouse. Further, the CIF may comprise an Extraction Transform Load (ETL) system for receiving the data from all the data sources and transforming it before loading it into the data warehouse. Further, the CIF may comprise one or more Data Marts that receive data from the Data Warehouse upon specific requests, the Data Marts each serving a specific purpose.
In view of the large amount of data and the many different software products processing the data, there may be a need for information about the software products processing all the data.